examples/grasp_stability.py

import numpy as np

from preprocessor.feature_extractor import MotokoFeatureExtractor


def predict_grasp_stability(signal: dict[str, np.ndarray]) -> str:
    extractor = MotokoFeatureExtractor.from_config("preprocessor/preprocessor_config.json")
    features = extractor(signal)
    stability_score = float(np.clip(features["input_values"].mean() + 0.5, 0.0, 1.0))
    return "stable" if stability_score >= 0.5 else "unstable"


if __name__ == "__main__":
    signal = {
        "force": np.random.randn(256, 3).astype(np.float32),
        "torque": np.random.randn(256, 3).astype(np.float32),
        "pressure": np.random.randn(256, 16).astype(np.float32),
        "vibration": np.random.randn(256, 6).astype(np.float32),
    }
    print("grasp:", predict_grasp_stability(signal))